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A sample of 33 lights in Austin gives an average of 46 cars/min while the city SD=3.4 A sample of 34 Dallas lights give a mean of 44 cars/mim with the city SD=1.4 At the 91% level, do the towns differ? 1. Is the test C 2. Critical Value 1.7210 3. Test statistic 3.1652 4. 3-decimal p-Value (A-Left Tailed, B-Right Tailed, C-2-Tailed) (separate with a comma if there are 2)

A sample of 33 lights in Austin gives an average of 46 cars/min while the city SD=3.4 A sample of 34 Dallas lights give a mean of 44 cars/mim with the city SD=1.4 At the 91% level, do the towns differ? 1. Is the test C 2. Critical Value 1.7210 3. Test statistic 3.1652 4. 3-decimal p-Value (A-Left Tailed, B-Right Tailed, C-2-Tailed) (separate with a comma if there are 2)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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**Statistical Analysis of Traffic Flow in Austin and Dallas** To investigate the traffic flow at signal lights in Austin and Dallas, we compare the average number of cars per minute passing through these lights. The data is based on samples from both cities and analyzed at the 91% confidence level to determine if there is a significant difference between the traffic flows in these two towns. ### Data Summary - **Austin Sample**: - Number of lights: 33 - Average cars per minute: 46 - Standard deviation (SD): 3.4 - **Dallas Sample**: - Number of lights: 34 - Average cars per minute: 44 - Standard deviation (SD): 1.4 ### Hypothesis Test 1. **Type of Test**: - The test is two-tailed, which means we are checking for any significant difference in either direction between the two means (Austin vs. Dallas). 2. **Critical Value**: - The critical value for this test, given the 91% confidence level, is 1.7210. This value is essential in determining the rejection region for the null hypothesis. 3. **Test Statistic**: - The calculated test statistic is 3.1652. This value indicates how many standard deviations our sample mean difference is away from the null hypothesis. 4. **P-Value**: - The three-decimal p-value needs to be calculated to understand the probability of observing the observed result under the null hypothesis. ### Interpretation A comparison of test statistics and the critical value will inform us whether to reject the null hypothesis, suggesting a significant difference in traffic flow rates between Austin and Dallas. The final p-value will provide further confirmation of the statistical significance of the test result.
Transcribed Image Text:**Statistical Analysis of Traffic Flow in Austin and Dallas** To investigate the traffic flow at signal lights in Austin and Dallas, we compare the average number of cars per minute passing through these lights. The data is based on samples from both cities and analyzed at the 91% confidence level to determine if there is a significant difference between the traffic flows in these two towns. ### Data Summary - **Austin Sample**: - Number of lights: 33 - Average cars per minute: 46 - Standard deviation (SD): 3.4 - **Dallas Sample**: - Number of lights: 34 - Average cars per minute: 44 - Standard deviation (SD): 1.4 ### Hypothesis Test 1. **Type of Test**: - The test is two-tailed, which means we are checking for any significant difference in either direction between the two means (Austin vs. Dallas). 2. **Critical Value**: - The critical value for this test, given the 91% confidence level, is 1.7210. This value is essential in determining the rejection region for the null hypothesis. 3. **Test Statistic**: - The calculated test statistic is 3.1652. This value indicates how many standard deviations our sample mean difference is away from the null hypothesis. 4. **P-Value**: - The three-decimal p-value needs to be calculated to understand the probability of observing the observed result under the null hypothesis. ### Interpretation A comparison of test statistics and the critical value will inform us whether to reject the null hypothesis, suggesting a significant difference in traffic flow rates between Austin and Dallas. The final p-value will provide further confirmation of the statistical significance of the test result.
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